Results 1 - 10 of 4,688

The X-tree: An index structure for high-dimensional data

by Stefan Berchtold, Daniel A. Keim, Hans-peter Kriegel - In Proceedings of the Int’l Conference on Very Large Data Bases , 1996
"... In this paper, we propose a new method for index-ing large amounts of point and spatial data in high-dimensional space. An analysis shows that index structures such as the R*-tree are not adequate for indexing high-dimensional data sets. The major problem of R-tree-based index structures is the over ..."
Abstract - Cited by 592 (17 self) - Add to MetaCart
and supernodes is to keep the directory as hi-erarchical as possible, and at the same time to avoid splits in the directory that would result in high over-lap. Our experiments show that for high-dimen-sional data, the X-tree outperforms the well-known R*-tree and the TV-tree by up to two orders of magnitude. 1.

OBB-Tree: A hierarchical structure for rapid interference detection

by S. Gottschalk, M. C. Lint, D. Manocha - PROC. ACM SIGGRAPH, 171–180 , 1996
"... We present a data structure and an algorithm for efficient and exact interference detection amongst complex models undergoing rigid motion. The algorithm is applicable to all general polygonal and curved models. It pre-computes a hierarchical representation of models using tight-fitting oriented bo ..."
Abstract - Cited by 845 (53 self) - Add to MetaCart
bounding box trees. At runtime, the algorithm traverses the tree and tests for overlaps between oriented bounding boxes based on a new separating axis theorem, which takes less than 200 operations in practice. It has been implemented and we compare its performance with other hierarchical data structures

Hierarchical mixtures of experts and the EM algorithm

by Michael I. Jordan, Robert A. Jacobs , 1993
"... We present a tree-structured architecture for supervised learning. The statistical model underlying the architecture is a hierarchical mixture model in which both the mixture coefficients and the mixture components are generalized linear models (GLIM’s). Learning is treated as a max-imum likelihood ..."
Abstract - Cited by 885 (21 self) - Add to MetaCart
We present a tree-structured architecture for supervised learning. The statistical model underlying the architecture is a hierarchical mixture model in which both the mixture coefficients and the mixture components are generalized linear models (GLIM’s). Learning is treated as a max-imum likelihood

Hierarchically Classifying Documents Using Very Few Words

by Daphne Koller, Mehran Sahami , 1997
"... The proliferation of topic hierarchies for text documents has resulted in a need for tools that automatically classify new documents within such hierarchies. Existing classification schemes which ignore the hierarchical structure and treat the topics as separate classes are often inadequate in text ..."
Abstract - Cited by 521 (8 self) - Add to MetaCart
The proliferation of topic hierarchies for text documents has resulted in a need for tools that automatically classify new documents within such hierarchies. Existing classification schemes which ignore the hierarchical structure and treat the topics as separate classes are often inadequate in text

The R*-tree: an efficient and robust access method for points and rectangles

by Norbert Beckmann, Hans-Peter Kriegel, Ralf Schneider, Bernhard Seeger - INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA , 1990
"... The R-tree, one of the most popular access methods for rectangles, is based on the heuristic optimization of the area of the enclosing rectangle in each inner node. By running numerous experiments in a standardized testbed under highly varying data, queries and operations, we were able to design the ..."
Abstract - Cited by 1262 (74 self) - Add to MetaCart
the R*-tree which incorporates a combined optimization of area, margin and overlap of each enclosing rectangle in the directory. Using our standardized testbed in an exhaustive performance comparison, it turned out that the R*-tree clearly outperforms the existing R-tree variants. Guttman's linear

Treemaps: a space-filling approach to the visualization of hierarchical information structures

by Brian Johnson, Ben Shneiderman - PROC. 2ND INTERNATIONAL VISUALIZATION CONFERENCE 1991. IEEE , 1991
"... This paper describes a novel method for the visualization of hierarchically structured information. The Tree-Map visualization technique makes 100 % use of the available display space, mapping the full hierarchy onto a rectangular region in a space-filling manner. This efficient use of space allows ..."
Abstract - Cited by 476 (26 self) - Add to MetaCart
This paper describes a novel method for the visualization of hierarchically structured information. The Tree-Map visualization technique makes 100 % use of the available display space, mapping the full hierarchy onto a rectangular region in a space-filling manner. This efficient use of space allows

Multicast Routing in Datagram Internetworks and Extended LANs

by Stephen E. Deering, David R. Cheriton - ACM Transactions on Computer Systems , 1990
"... Multicasting, the transmission of a packet to a group of hosts, is an important service for improving the efficiency and robustness of distributed systems and applications. Although multicast capability is available and widely used in local area networks, when those LANs are interconnected by store- ..."
Abstract - Cited by 1074 (5 self) - Add to MetaCart
describe modifications to the single-spanning-tree routing algorithm commonly used by link-layer bridges, to reduce the costs of multicasting in large extended LANs. Finally, we discuss how the use of multicast scope control and hierarchical multicast routing allows the multicast service to scale up

Scalable Application Layer Multicast

by Suman Banerjee, Bobby Bhattacharjee, Christopher Kommareddy , 2002
"... We describe a new scalable application-layer multicast protocol, specifically designed for low-bandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the application-layer multicast peers and can support a number of different data deliv ..."
Abstract - Cited by 731 (21 self) - Add to MetaCart
We describe a new scalable application-layer multicast protocol, specifically designed for low-bandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the application-layer multicast peers and can support a number of different data

Model-Based Analysis of Oligonucleotide Arrays: Model Validation, Design Issues and Standard Error Application

by Cheng Li, Wing Hung Wong , 2001
"... Background: A model-based analysis of oligonucleotide expression arrays we developed previously uses a probe-sensitivity index to capture the response characteristic of a specific probe pair and calculates model-based expression indexes (MBEI). MBEI has standard error attached to it as a measure of ..."
Abstract - Cited by 775 (28 self) - Add to MetaCart
better ranking statistic for filtering genes. We can assign reliability indexes for genes in a specific cluster of interest in hierarchical clustering by resampling clustering trees. A software dChip implementing many of these analysis methods is made available. Conclusions: The model-based approach

Dynamic Bayesian Networks: Representation, Inference and Learning

by Kevin Patrick Murphy , 2002
"... Modelling sequential data is important in many areas of science and engineering. Hidden Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they are simple and flexible. For example, HMMs have been used for speech recognition and bio-sequence analysis, and KFMs have bee ..."
Abstract - Cited by 770 (3 self) - Add to MetaCart
sequential data. In particular, the main novel technical contributions of this thesis are as follows: a way of representing Hierarchical HMMs as DBNs, which enables inference to be done in O(T) time instead of O(T 3), where T is the length of the sequence; an exact smoothing algorithm that takes O(log T
Results 1 - 10 of 4,688